The following pages link to (Q5396663):
Displaying 34 items.
- Calibrating covariate informed product partition models (Q65541) (← links)
- A fully nonparametric modeling approach to binary regression (Q273642) (← links)
- Scalable Bayesian nonparametric regression via a Plackett-Luce model for conditional ranks (Q309544) (← links)
- Information value in nonparametric Dirichlet-process Gaussian-process (DPGP) mixture models (Q340712) (← links)
- A tutorial on Bayesian nonparametric models (Q423105) (← links)
- Nonparametric Bayes classification and hypothesis testing on manifolds (Q444946) (← links)
- Optimal learning with a local parametric belief model (Q746825) (← links)
- A Bayesian nonparametric model and its application in insurance loss prediction (Q784420) (← links)
- Matrix-variate Dirichlet process priors with applications (Q899020) (← links)
- Dual-semiparametric regression using weighted Dirichlet process mixture (Q1662051) (← links)
- Infinite max-margin factor analysis via data augmentation (Q1669779) (← links)
- Semiparametric Bayesian multiple imputation for regression models with missing mixed continuous-discrete covariates (Q2183768) (← links)
- Bayesian subgroup analysis in regression using mixture models (Q2242036) (← links)
- Supervised learning via smoothed Polya trees (Q2303053) (← links)
- A tutorial on Dirichlet process mixture modeling (Q2332845) (← links)
- Bayesian semiparametric Wiener system identification (Q2356659) (← links)
- Hybrid Dirichlet mixture models for functional data (Q2920281) (← links)
- A predictive study of Dirichlet process mixture models for curve fitting (Q2922155) (← links)
- A Recursive Local Polynomial Approximation Method Using Dirichlet Clouds and Radial Basis Functions (Q3186111) (← links)
- Optimal Learning with Local Nonlinear Parametric Models over Continuous Designs (Q3303989) (← links)
- Dirichlet Processes in Nonlinear Mixed Effects Models (Q3577178) (← links)
- Computations of Mixtures of Dirichlet Processes (Q3742594) (← links)
- Marginal Likelihood and Bayes Factors for Dirichlet Process Mixture Models (Q4468540) (← links)
- Bayesian Inference for Linear Dynamic Models With Dirichlet Process Mixtures (Q4567605) (← links)
- On expectation propagation for generalised, linear and mixed models (Q4639816) (← links)
- Bayesian density regression for discrete outcomes (Q5117661) (← links)
- <i>i</i>Fusion: Individualized Fusion Learning (Q5120662) (← links)
- Generalized spatial stick-breaking processes (Q5867488) (← links)
- A Bayesian nonparametric model for zero‐inflated outcomes: Prediction, clustering, and causal estimation (Q6047796) (← links)
- Functional clustering methods for binary longitudinal data with temporal heterogeneity (Q6170537) (← links)
- Semiparametric Bayes instrumental variable estimation with many weak instruments (Q6541759) (← links)
- Dirichlet process mixture models with shrinkage prior (Q6541784) (← links)
- A practical introduction to Bayesian estimation of causal effects: parametric and nonparametric approaches (Q6627906) (← links)
- Covariate-Dependent Clustering of Undirected Networks with Brain-Imaging Data (Q6637467) (← links)
